Scholarly Works, Economics

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Research articles, presentations, and other scholarship

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Applications of land value taxation to problems of environmental protection, congestion, efficient resource use, population, and economic growth
Tideman, Nicolaus (Lincoln Institute of Land Policy, 1998)
When economists think about the contribution that land value taxation might make to economic performance, they are likely to think in terms of property tax reform. If taxes on structures are reduced or eliminated, one can expect that more structures will be built, and cities will be taller, more compact and more efficient. But more efficient cities are only the beginning of the contribution that land value taxation can make to improving economic performance. Land value taxation can be generalized to the principle that people should pay for all of their appropriations of natural opportunities, according to the opportunity costs of those appropriations, and the resulting revenue should be shared equally. There are important applications of this principle to questions of environmental protection, relieving congestion, efficient resource use, population growth, and general economic growth. This paper discusses these more varied applications of the generalized principle of land value taxation. The paper begins with a discussion of the justifications of land value taxation. It then applies land value taxation successively to problems of environmental protection, congestion, efficient use of renewable and non-renewable natural resources, and population growth. Then it discusses the contribution of land value taxation to economic growth, and an estimate of the magnitude of that contribution.
Elliptically Symmetric Principal Component Analysis: Modeling Temporal/contemporaneous Dependence Using Non-gaussian Distributions
Solat, Karo; Spanos, Aris (2018-05-16)
The primary objective of this paper is to extend the classical principal component analysis (PCA), aiming to reduce the dimensionality of a large number of Normal interrelated variables, in two directions: The rst is to go beyond the static (contem- poraneous or synchronous) covariance matrix among these interrelated variables to include certain forms of temporal (over time) dependence. The second direction takes the form of extending the PCA model beyond the multivariate normal distribution to the elliptically symmetric family of distributions, including the Normal, Student's t, the Laplace, and the Pearson type II distributions as special cases. The result of these extensions is called the elliptically symmetric principal component analysis (ESPCA), which is illustrated using Monte Carlo simulations to demonstrate the enhanced relia- bility of these more general factor models in the context of out-of-sample forecasting.
Rural electrification and fertility decline in Iran
Salehi-Isfahani, Djavad; Taghvatalab, Sara (Cambridge University Press, 2026-01-07)
A growing body of evidence finds that rural electrification reduces fertility, typically by expanding women’s opportunities outside the home and raising the opportunity cost of childbearing. We examine electrification in post-revolutionary rural Iran, where electricity expanded rapidly but female labor force participation remained low. Using a large panel of villages observed in the 1986, 1996, and 2006 censuses, we show that while Ordinary Least Squares estimates align with the broader literature in suggesting a negative association between electrification and fertility, instrumental variable estimates exploiting elevation-based variation reveal the opposite: villages with longer exposure to electricity experienced higher fertility. This positive effect is strongest in provinces with lower female labor force participation, indicating that the substitution channel emphasized in prior research was weak in the Iranian context. These findings highlight the importance of context in shaping demographic responses to infrastructure and suggest that electrification’s effects on fertility are not universally negative.
Care cascade of hypertension across stages among older adults in India
Sahoo, Umakanta; Maiti, Suraj; Mohanty, Sanjay K. (Public Library of Science, 2025-12-03)
Hypertension is now a common disease and the single largest risk factor for premature mortality in India. Hypertensive individuals are not homogenous and have varying risks to life. Although the number of studies on the care cascade of hypertension in India is increasing, no attempts have been made to estimate the prevalence and cascade of care across different stages of hypertension. This study estimates the prevalence, awareness, and treatment of hypertension by stages of hypertension among older adults in India. We analyzed data on 58,787 adults aged 45 years and above from the Longitudinal Ageing Study in India (LASI), Wave 1 (2017−18). Hypertension stages were categorized in accordance with the classification given by the Ministry of Health and Family Welfare, Government of India, and regrouped as per global classification. The age-sex adjusted prevalence, awareness, and treatment rates for different stages of hypertension were estimated. Multinomial logistic regression and the Erreygers’ Concentration Index were used to assess socioeconomic inequalities in hypertension care. We estimated the prevalence of pre-hypertension at 39.9%, stage 1 hypertension at 22.1% and stage 2 hypertension at 9.9%. Increasing age and body mass index were associated with a higher chance of hypertension, whereas living with spouses and children meant having lower odds of hypertension across all stages. The economic condition of the household, educational attainment, and social groups were not significant predictors of hypertension across the stages. The awareness and treatment of hypertension were low across all the stages. The Erreygers’ Concentration Index on awareness and treatment was pro-rich across all the stages of hypertension. A large proportion of hypertensive patients at the advanced stage remain undiagnosed and untreated and carry a higher risk of premature mortality. The awareness and treatment of hypertension are lower among the poorer and socially disadvantaged populations than their richer and more privileged counterparts across all stages.
Impacts of Financial Literacy Training on Refugee Youth Outcomes
Das, Nandini; Gupta, Anubhab; Mingo, Cristobal; Zhu, Heng (Routledge, 2025-04-14)
As humanitarian assistance from international organizations transitions from in-kind- to cash- aid, and increasingly through digital payments, the importance of digital financial literacy to complement cash transfer programs has grown significantly. This paper evaluates the impact of a financial literacy training program on refugee youth outcomes in Uganda. We adopt an approach that closely emulates a natural experiment by leveraging the staggered geographic rollout of the program to identify its impacts. Using reduced-form econometric analyses, robust to various specifications, we find that participation in the training program is associated with significant positive effects on financial knowledge and financial behavior among young refugees. The findings are important because financial knowledge is essential for saving decisions, responsible borrowing, business operations, and various other life goals among refugees. Our results also suggest that the training program boosted youth’s confidence in terms of integrating with the host population.
Berge equilibrium, altruism and social welfare
Haller, Hans (Springer, 2024-06-01)
Welfare and other properties of Berge equilibria are investigated. In particular, we address the questions to what extent Berge equilibrium can select from multiple Nash equilibria; can serve as a substitute for Nash equilibria; can Pareto improve upon Nash equilibrium. Furthermore, some of the recent results on the relation between Berge equilibria and Kantian equilibria are summarized.
Socioeconomic inequality in awareness, treatment and control of diabetes among adults in India: Evidence from National Family Health Survey of India (NFHS), 2019-2021
Maiti, Suraj; Akhtar, Shamrin; Upadhyay, Ashish Kumar; Mohanty, Sanjay K. (Nature Portfolio, 2023-02-20)
Diabetes is a growing epidemic and a major threat to most of the households in India. Yet, there is little evidence on the extent of awareness, treatment, and control (ATC) among adults in the country. In this study, we estimate the prevalence and ATC of diabetes among adults across various sociodemographic groups and states of India. We used data on 2,078,315 individuals aged 15 years and over from the recent fifth round, the most recent one, of the National Family Health Survey (NFHS-5), 2019–2021, that was carried out across all the states of India. Diabetic individuals were identified as those who had random blood glucose above 140 mg/dL or were taking diabetes medication or has doctor-diagnosed diabetes. Diabetic individuals who reported diagnosis were labelled as aware, those who reported taking medication for controlling blood glucose levels were labelled as treated and those whose blood glucose levels were < 140 mg/dL were labelled as controlled. The estimates of prevalence of diabetes, and ATC were age-sex adjusted and disaggregated by household wealth quintile, education, age, sex, urban–rural residence, caste, religion, marital status, household size, and state. Concentration index was used to quantify socioeconomic inequalities and multivariable logistic regression was used to estimate the adjusted differences in those outcomes. We estimated diabetes prevalence to be 16.1% (15.9–16.1%). Among those with diabetes, 27.5% (27.1–27.9%) were aware, 21.5% (21.1–21.7%) were taking treatment and 7% (6.8–7.1%) had their diabetes under control. Across the states of India, the adjusted rates of awareness varied from 14.4% (12.1–16.8%) to 54.4% (40.3–68.4%), of treatment from 9.3% (7.5–11.1%) to 41.2% (39.9–42.6%), and of control from 2.7% (1.6–3.7%) to 11.9% (9.7–14.0%). The age-sex adjusted rates were lower (p < 0.001) among the poorer and less educated individuals as well as among males, residents of rural areas, and those from the socially backward groups Among individuals with diabetes, the richest fifth were respectively 12.4 percentage points (pp) (11.3–13.4; p < 0.001), 10.5 pp (9.7–11.4; p < 0.001), and 2.3 pp (1.6–3.0; p < 0.001) more likely to be aware, getting treated, and having diabetes under control, than the poorest fifth. The concentration indices of ATC were 0.089 (0.085–0.092), 0.083 (0.079–0.085) and 0.017 (0.015–0.018) respectively. Overall, the ATC of diabetes is low in India. It is especially low the poorer and the less educated individuals. Targeted interventions and management can reduce the diabetes burden in India.
Women’s empowerment and nutritional outcomes in India
Dutta, Susmita; Dutta, Ajay; Maiti, Suraj (Nature Portfolio, 2025-12-01)
Women’s nutritional health is significantly influenced by their social standing, especially in low- and middle-income countries where patriarchal structures restrict women’s decision-making. In India, women have limited autonomy over personal and domestic matters, which restricts their decision-making power and access to resources. In this context, this study investigates the relationship between women’s empowerment and their nutritional health in India. We used nationally representative data from the most recent iteration of the National Family Health Survey (NFHS-5), 2019–2021. Women’s autonomy was measured using a composite Women’s Autonomy Index (WAI), encompassing decision-making power, asset ownership, and freedom of movement. Logistic regression models were used to estimate the association between WAI and underweight (BMI < 18.5 kg/m²), controlling for sociodemographic and household factors. Robustness checks were performed, which included modelling continuous BMI, using alternative autonomy specifications (WAI Modified), and performing stratified analysis by urban–rural residence. A total of 14.0% (95% CI 13.6, 14.4%) of the study participants were underweight. Higher autonomy was associated with significantly lower odds of being underweight (adjusted OR: 0.951; 95% CI 0.923, 0.980). The margins analysis indicated that the predicted underweight prevalence was 9.5% among women with the highest autonomy scores compared to 16.3% among those with no/low autonomy. Continuous BMI models showed a positive gradient, with BMI increasing by approximately 1.5 kg/m² across the full range of autonomy scores. Stratified analysis revealed stronger autonomy effects in urban areas. These associations remained robust when we used an expanded autonomy measure that incorporated joint decision-making. Women’s age, educational status, work status, husband’s educational level, place of residence, household size, and household wealth were strong predictors of women’s nutritional status. We find a strong association between women’s autonomy and nutritional status, with higher autonomy reducing the risk of undernutrition. In addition, regional and socioeconomic disparities are also factors that affect women’s nutritional status. Policy interventions that ameliorate women’s decision-making power, asset control, and mobility can effectively address undernutrition among women and promote broader health gains.
The intermittent Phillips curve: Finding a stable (but persistence-dependent) Phillips curve model specification
Ashley, Richard A.; Verbrugge, Randal (Wiley, 2025-07)
We make substantial progress on understanding the Phillips curve, yielding important monetary policy implications. Inflation responds differently to persistent versus moderately persistent (or transient) fluctuations in the unemployment gap. This persistence-dependent relationship aligns with business-cycle stages, and is consistent with existing theory. Previous work fails to model this dependence, thereby finding the numerous “inflation puzzles”—for example, missing inflation/disinflation—noted in the literature. Our specification eliminates these puzzles; for example, the Phillips curve has not weakened; inflation's post-2012 slow upward trudge was predictable. The model's coefficients are stable, and it provides accurate out-of-sample conditional recursive forecasts through the Great Recession and recovery.
Revisiting the Replication Crisis and the Untrustworthiness of Empirical Evidence
Spanos, Aris (MDPI, 2025-05-20)
The current replication crisis relating to the non-replicability and the untrustworthiness of published empirical evidence is often viewed through the lens of the Positive Predictive Value (PPV) in the context of the Medical Diagnostic Screening (MDS) model. The PPV is misconstrued as a measure that evaluates ‘the probability of rejecting H0 when false’, after being metamorphosed by replacing its false positive/negative probabilities with the type I/II error probabilities. This perspective gave rise to a widely accepted diagnosis that the untrustworthiness of published empirical evidence stems primarily from abuses of frequentist testing, including p-hacking, data-dredging, and cherry-picking. It is argued that the metamorphosed PPV misrepresents frequentist testing and misdiagnoses the replication crisis, promoting ill-chosen reforms. The primary source of untrustworthiness is statistical misspecification: invalid probabilistic assumptions imposed on one’s data. This is symptomatic of the much broader problem of the uninformed and recipe-like implementation of frequentist statistics without proper understanding of (a) the invoked probabilistic assumptions and their validity for the data used, (b) the reasoned implementation and interpretation of the inference procedures and their error probabilities, and (c) warranted evidential interpretations of inference results. A case is made that Fisher’s model-based statistics offers a more pertinent and incisive diagnosis of the replication crisis, and provides a well-grounded framework for addressing the issues (a)–(c), which would unriddle the non-replicability/untrustworthiness problems.
Understanding the Effects of a Math Placement Exam on Calculus 1 Enrollment and Engineering Persistence
Ryan, Olivia; Sajadi, Susan; Barrera, Sergio; Jaghargh, Reza Tavakoli (MDPI, 2025-01-26)
Educational institutions are grappling with declining enrollments and low mathematical achievements. This study investigates how a math placement exam (ALEKS) influences enrollment in Calculus 1 and student persistence, taking into account academic preparation and demographic factors. It also evaluates the effects of remedial math courses for students near the placement cutoff. Using Astin’s input–environment–outcome model, this study analyzed data from 3380 students employing a Kitagawa-Oaxaca-Blinder decomposition and fuzzy regression discontinuity. These methods were used to identify unexplained differences across demographic groups and capture outcomes near the math placement cutoff. Based on the findings, a cutoff of 80% for the ALEKS exam is appropriate. This study underscores the role of math placement exams in shaping engineering enrollment and student success. These findings prompt reevaluating placement strategies and support mechanisms, particularly for URM, first-generation, and female students, to enhance equity and retention in engineering.
Merge-Proofness and Cost Solidarity in Shortest Path Games
Bahel, Eric; Gómez-Rúa, María; Vidal-Puga, Juan (Springer, 2025-02)
We study cost-sharing rules in network problems where agents seek to ship quantities of some good to their respective locations, and the cost on each arc is linear in the flow crossing it. In this context, Core Selection requires that each subgroup of agents pay a joint cost share that is not higher than its stand-alone cost. We prove that the demander rule, under which each agent pays the cost of her shortest path for each unit she demands, is the unique cost-sharing rule satisfying both Core Selection and Merge Proofness. The Merge Proofness axiom prevents distinct nodes from reducing their joint cost share by merging into a single node. An alternative characterization of the demander rule is obtained by combining Core Selection and Cost Solidarity. The Cost Solidarity axiom says that each agent’s cost share should be weakly increasing in the cost matrix.
A geometric approach for accelerating neural networks designed for classification problems
Saffar, Mohsen; Kalhor, Ahmad; Habibnia, Ali (Nature Portfolio, 2024-07-30)
This paper proposes a geometric-based technique for compressing convolutional neural networks to accelerate computations and improve generalization by eliminating non-informative components. The technique utilizes a geometric index called separation index to evaluate the functionality of network elements such as layers and filters. By applying this index along with center-based separation index, a systematic algorithm is proposed that optimally compresses convolutional and fully connected layers. The algorithm excludes layers with low performance, selects the best subset of filters in the filtering layers, and tunes the parameters of fully connected layers using center-based separation index. An illustrative example of classifying CIFAR-10 dataset is presented to explain the algorithm step-by-step. The proposed method achieves impressive pruning results on networks trained by CIFAR-10 and ImageNet datasets, with 87.5%, 77.6%, and 78.8% of VGG16, GoogLeNet, and DenseNet parameters pruned, respectively. Comparisons with state-of-the-art works are provided to demonstrate the effectiveness of the proposed method.
Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning
Camerer, Colin F.; Nave, Gideon; Smith, Alec C. (INFORMS (Institute for Operations Research and Management Sciences), 2018-05)
We study dynamic unstructured bargaining with deadlines and one-sided private information about the amount available to share (the "pie size"). Using mechanism design theory, we show that given the players' incentives, the equilibrium incidence of bargaining failures ("strikes'') should increase with the pie size, and we derive a condition under which strikes are efficient. In our setting, no equilibrium satisfies both equality and efficiency in all pie sizes. We derive two equilibria that resolve the trade-off between equality and efficiency by either favoring equality or favoring efficiency. Using a novel experimental paradigm, we confirm that strike incidence is decreasing in the pie size. Subjects reach equal splits in small pie games (in which strikes are efficient), while most payoffs are close to either the efficient or the equal equilibrium prediction, when the pie is large. We employ a machine learning approach to show that bargaining process features recorded early in the game improve out of sample prediction of disagreements at the deadline. The process feature predictions are as accurate as predictions from pie sizes only, and adding process and pie data together improves predictions even more.
Enumerating rights: more is not always better
Ball, Sheryl B.; Dave, Chetan; Dodds, Stefan (Springer, 2023-05-11)
Contemporary political and policy debate rhetoric increasingly employs the language of ‘rights’: how they are assigned and what entitlements individuals in a society are due. While the obvious constitution design issues surround how rights enumeration affects the relationship between a government and its citizens, we instead analyze how rights framing impacts how citizens interact with each other. We design and implement a novel experiment to test whether social cooperation depends on the enumeration and positive or negative framing of the right of subjects to take a particular action. We find that when rights are framed positively, there exists an ‘entitlement effect’ that reduces social cooperation levels and crowds-out the tendency of individuals to act pro-socially.
Vaccine Hesitancy and Betrayal Aversion
Alsharawy, Abdelaziz; Dwibedi, Esha; Aimone, Jason; Ball, Sheryl B. (Springer, 2022-05-17)
The determinants of vaccine hesitancy remain complex and context specific. Betrayal aversion occurs when an individual is hesitant to risk being betrayed in an environment involving trust. In this pre-registered vignette experiment, we show that betrayal aversion is not captured by current vaccine hesitancy measures despite representing a significant source of unwillingness to be vaccinated. Our survey instrument was administered to 888 United States residents via Amazon Mechanical Turk in March 2021. We find that over a third of participants have betrayal averse preferences, resulting in an 8–26% decline in vaccine acceptance, depending on the betrayal source. Interestingly, attributing betrayal risk to scientists or government results in the greatest declines in vaccine acceptance. We explore an exogenous message intervention and show that an otherwise effective message acts narrowly and fails to reduce betrayal aversion. Our results demonstrate the importance of betrayal aversion as a preference construct in the decision to vaccinate.
The Ashley and Patterson (1986) test for serial independence in daily stock returns, revisited
Ashley, Richard A.; Najafi, Faezeh (Springer, 2024-11-22)
We update and extend the non-parametric test proposed in Ashley and Patterson (J Financ Quant Anal 21:221–227, 2014) – of the proposition that the (pre-whitened) daily stock returns for a firm are serially independent, and hence unpredictable from their own past. That paper applied this test to daily returns from 1962 to 1981 for several U.S. corporations and aggregate indices, finding mixed evidence against this null hypothesis of serial independence. The returns dataset is updated here to include thirteen firms which are currently more relevant, and the sample is extended through the end of 2023. We also update the simulation methodology here to properly account for the conditional heteroskedasticity in the daily returns data, so that the present results should now be more statistically reliable. The results are broadly in line with our earlier results, but they do suggest further avenues of research in this area.
A model of the formation of multilayer networks
Billand, Pascal; Bravard, Christophe; Joshi, Sumit; Mahmud, Ahmed Saber; Sarangi, Sudipta (Elsevier, 2023-10)
We study the formation of multilayer networks where payoffs are determined by the degrees of players in each network. We begin by imposing either concavity or convexity in degree on the payoff function of the players. We then explore distinct network relationships that result from inter- and intra-network spillovers captured by the properties of supermodularity/submodularity and strategic complementarity respectively. We show the existence of equilibria and characterize them. Additionally, we establish both necessary and sufficient conditions for an equilibrium to occur. We also highlight the connection, in equilibrium, between inter-network externalities and the identity of linked players in one network given the identity of linked players in the other network. Furthermore, we analyze efficient multilayer networks. Finally, we extend our models to contexts with more than two layers, and scenarios where agents receive a bonus for being connected to the same individuals in both networks.
ChatGPT has Aced the Test of Understanding in College Economics: Now What?
Geerling, Wayne; Mateer, G. Dirk; Damodaran, Nikhil; Wooten, Jadrian (SAGE, 2023-04-08)
The Test of Understanding in College Economics (TUCE) is a standardized test of economics knowledge performed in the United States which primarily targets principles-level understanding. We asked ChatGPT to complete the TUCE. ChatGPT ranked in the 91st percentile for Microeconomics and the 99th percentile for Macroeconomics when compared to students who take the TUCE exam at the end of their principles course. The results show that ChatGPT is capable of providing answers that exceed the mean responses of students across all institutions. The emergence of artificial intelligence presents a significant challenge to traditional assessment methods in higher education. An important implication of this finding is that educators will likely need to redesign their curriculum in at least one of the following three ways: reintroduce proctored, in-person assessments; augment learning with chatbots; and/or increase the prevalence of experiential learning projects that artificial intelligence struggles to replicate well.
Assessing proxies of knowledge and difficulty with rubric‐based instruments
Smith, Ben O.; Wooten, Jadrian (Wiley, 2023-09-28)
The fields of psychometrics, economic education, and education have developed statistically‐valid methods of assessing knowledge and learning. These methods include item response theory, value‐added learning models, and disaggregated learning. These methods, however, focus on multiple‐choice or single response assessments. Faculty and administrators routinely assess knowledge through papers, thesis presentations, or other demonstrations of knowledge assessed with rubric rows. This paper presents a statistical approach to estimating a proxy for student ability and rubric row difficulty. Moreover, we have developed software so that practitioners can more easily apply this method to their instruments. This approach can be used in researching education treatment effects, practitioners measuring learning outcomes in their own classrooms, or estimating knowledge for administrative assessment. As an example, we have applied these new methods to projects in a large Labor Economics course at a public university.

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